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Author

Kadri Põldmaa

Bio: Kadri Põldmaa is an academic researcher from University of Tartu. The author has contributed to research in topics: Genus & Hypomyces. The author has an hindex of 16, co-authored 43 publications receiving 4839 citations. Previous affiliations of Kadri Põldmaa include American Museum of Natural History.
Topics: Genus, Hypomyces, Monophyly, Biology, Helotiales

Papers
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Journal ArticleDOI
TL;DR: All fungal species represented by at least two ITS sequences in the international nucleotide sequence databases are now given a unique, stable name of the accession number type, and the term ‘species hypothesis’ (SH) is introduced for the taxa discovered in clustering on different similarity thresholds.
Abstract: The nuclear ribosomal internal transcribed spacer (ITS) region is the formal fungal barcode and in most cases the marker of choice for the exploration of fungal diversity in environmental samples. Two problems are particularly acute in the pursuit of satisfactory taxonomic assignment of newly generated ITS sequences: (i) the lack of an inclusive, reliable public reference data set and (ii) the lack of means to refer to fungal species, for which no Latin name is available in a standardized stable way. Here, we report on progress in these regards through further development of the UNITE database (http://unite.ut.ee) for molecular identification of fungi. All fungal species represented by at least two ITS sequences in the international nucleotide sequence databases are now given a unique, stable name of the accession number type (e.g. Hymenoscyphus pseudoalbidus|GU586904|SH133781.05FU), and their taxonomic and ecological annotations were corrected as far as possible through a distributed, third-party annotation effort. We introduce the term ‘species hypothesis’ (SH) for the taxa discovered in clustering on different similarity thresholds (97–99%). An automatically or manually designated sequence is chosen to represent each such SH. These reference sequences are released (http://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and in the QIIME pipeline. The system and the data will be updated automatically as the number of public fungal ITS sequences grows. We invite everybody in the position to improve the annotation or metadata associated with their particular fungal lineages of expertise to do so through the new Web-based sequence management system in UNITE.

2,605 citations

Journal ArticleDOI
28 Nov 2014-Science
TL;DR: Diversity of most fungal groups peaked in tropical ecosystems, but ectomycorrhizal fungi and several fungal classes were most diverse in temperate or boreal ecosystems, and manyfungal groups exhibited distinct preferences for specific edaphic conditions (such as pH, calcium, or phosphorus).
Abstract: Fungi play major roles in ecosystem processes, but the determinants of fungal diversity and biogeographic patterns remain poorly understood. Using DNA metabarcoding data from hundreds of globally distributed soil samples, we demonstrate that fungal richness is decoupled from plant diversity. The plant-to-fungus richness ratio declines exponentially toward the poles. Climatic factors, followed by edaphic and spatial variables, constitute the best predictors of fungal richness and community composition at the global scale. Fungi show similar latitudinal diversity gradients to other organisms, with several notable exceptions. These findings advance our understanding of global fungal diversity patterns and permit integration of fungi into a general macroecological framework.

2,346 citations

Journal ArticleDOI
TL;DR: The web-based workbench PlutoF is described, which is designed to bridge the gap between the needs of contemporary research in biology and the existing software resources and databases.
Abstract: DNA sequences accumulating in the International Nucleotide Sequence Databases (INSD) form a rich source of information for taxonomic and ecological meta-analyses. However, these databases include many erroneous entries, and the data itself is poorly annotated with metadata, making it difficult to target and extract entries of interest with any degree of precision. Here we describe the web-based workbench PlutoF, which is designed to bridge the gap between the needs of contemporary research in biology and the existing software resources and databases. Built on a relational database, PlutoF allows remote-access rapid submission, retrieval, and analysis of study, specimen, and sequence data in INSD as well as for private datasets though web-based thin clients. In contrast to INSD, PlutoF supports internationally standardized terminology to allow very specific annotation and linking of interacting specimens and species. The sequence analysis module is optimized for identification and analysis of environmental ITS sequences of fungi, but it can be modified to operate on any genetic marker and group of organisms. The workbench is available at http://plutof.ut.ee.

258 citations

Journal ArticleDOI
Sergei Põlme1, Sergei Põlme2, Kessy Abarenkov1, R. Henrik Nilsson3, Björn D. Lindahl4, Karina E. Clemmensen4, Håvard Kauserud5, Nhu H. Nguyen6, Rasmus Kjøller7, Scott T. Bates8, Petr Baldrian9, Tobias Guldberg Frøslev7, Kristjan Adojaan2, Alfredo Vizzini10, Ave Suija2, Donald H. Pfister11, Hans Otto Baral, Helle Järv12, Hugo Madrid13, Hugo Madrid14, Jenni Nordén, Jian-Kui Liu15, Julia Pawłowska16, Kadri Põldmaa2, Kadri Pärtel2, Kadri Runnel2, Karen Hansen17, Karl-Henrik Larsson, Kevin D. Hyde18, Marcelo Sandoval-Denis, Matthew E. Smith19, Merje Toome-Heller20, Nalin N. Wijayawardene, Nelson Menolli21, Nicole K. Reynolds19, Rein Drenkhan22, Sajeewa S. N. Maharachchikumbura15, Tatiana Baptista Gibertoni23, Thomas Læssøe7, William J. Davis24, Yuri Tokarev, Adriana Corrales25, Adriene Mayra Soares, Ahto Agan2, A. R. Machado23, Andrés Argüelles-Moyao26, Andrew P. Detheridge, Angelina de Meiras-Ottoni23, Annemieke Verbeken27, Arun Kumar Dutta28, Bao-Kai Cui29, C. K. Pradeep, César Marín30, Daniel E. Stanton, Daniyal Gohar2, Dhanushka N. Wanasinghe31, Eveli Otsing2, Farzad Aslani2, Gareth W. Griffith, Thorsten Lumbsch32, Hans-Peter Grossart33, Hans-Peter Grossart34, Hossein Masigol35, Ina Timling36, Inga Hiiesalu2, Jane Oja2, John Y. Kupagme2, József Geml, Julieta Alvarez-Manjarrez26, Kai Ilves2, Kaire Loit22, Kalev Adamson22, Kazuhide Nara37, Kati Küngas2, Keilor Rojas-Jimenez38, Krišs Bitenieks39, Laszlo Irinyi40, Laszlo Irinyi41, Laszlo Nagy, Liina Soonvald22, Li-Wei Zhou31, Lysett Wagner33, M. Catherine Aime8, Maarja Öpik2, María Isabel Mujica30, Martin Metsoja2, Martin Ryberg42, Martti Vasar2, Masao Murata37, Matthew P. Nelsen32, Michelle Cleary4, Milan C. Samarakoon18, Mingkwan Doilom31, Mohammad Bahram4, Mohammad Bahram2, Niloufar Hagh-Doust2, Olesya Dulya2, Peter R. Johnston43, Petr Kohout9, Qian Chen31, Qing Tian18, Rajasree Nandi44, Rasekh Amiri2, Rekhani H. Perera18, Renata dos Santos Chikowski23, Renato Lucio Mendes-Alvarenga23, Roberto Garibay-Orijel26, Robin Gielen2, Rungtiwa Phookamsak31, Ruvishika S. Jayawardena18, Saleh Rahimlou2, Samantha C. Karunarathna31, Saowaluck Tibpromma31, Shawn P. Brown45, Siim-Kaarel Sepp2, Sunil Mundra5, Sunil Mundra46, Zhu Hua Luo47, Tanay Bose48, Tanel Vahter2, Tarquin Netherway4, Teng Yang31, Tom W. May49, Torda Varga, Wei Li50, Victor R. M. Coimbra23, Virton Rodrigo Targino de Oliveira23, Vitor Xavier de Lima23, Vladimir S. Mikryukov2, Yong-Zhong Lu51, Yosuke Matsuda52, Yumiko Miyamoto53, Urmas Kõljalg2, Urmas Kõljalg1, Leho Tedersoo2, Leho Tedersoo1 
American Museum of Natural History1, University of Tartu2, University of Gothenburg3, Swedish University of Agricultural Sciences4, University of Oslo5, University of Hawaii at Manoa6, University of Copenhagen7, Purdue University8, Academy of Sciences of the Czech Republic9, University of Turin10, Harvard University11, Synlab Group12, Universidad Mayor13, Universidad Santo Tomás14, University of Electronic Science and Technology of China15, University of Warsaw16, Swedish Museum of Natural History17, Mae Fah Luang University18, University of Florida19, Laos Ministry of Agriculture and Forestry20, São Paulo Federal Institute of Education, Science and Technology21, Estonian University of Life Sciences22, Federal University of Pernambuco23, United States Department of Energy24, Del Rosario University25, National Autonomous University of Mexico26, Ghent University27, West Bengal State University28, Beijing Forestry University29, Pontifical Catholic University of Chile30, Chinese Academy of Sciences31, Field Museum of Natural History32, Leibniz Association33, University of Potsdam34, University of Gilan35, University of Alaska Fairbanks36, University of Tokyo37, University of Costa Rica38, Forest Research Institute39, Westmead Hospital40, University of Sydney41, Uppsala University42, Landcare Research43, University of Chittagong44, University of Memphis45, United Arab Emirates University46, Ministry of Land and Resources of the People's Republic of China47, University of Pretoria48, Royal Botanic Gardens49, Ocean University of China50, Guizhou University51, Mie University52, Hokkaido University53
TL;DR: Fungal traits and character database FungalTraits operating at genus and species hypothesis levels is presented in this article, which includes 17 lifestyle related traits of fungal and Stramenopila genera.
Abstract: The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies. Over the past decades, rapid development and affordability of molecular tools have tremendously improved insights of the fungal diversity in all ecosystems and habitats. Yet, in spite of the progress of molecular methods, knowledge about functional properties of the fungal taxa is vague and interpretation of environmental studies in an ecologically meaningful manner remains challenging. In order to facilitate functional assignments and ecological interpretation of environmental studies we introduce a user friendly traits and character database FungalTraits operating at genus and species hypothesis levels. Combining the information from previous efforts such as FUNGuild and Fun(Fun) together with involvement of expert knowledge, we reannotated 10,210 and 151 fungal and Stramenopila genera, respectively. This resulted in a stand-alone spreadsheet dataset covering 17 lifestyle related traits of fungal and Stramenopila genera, designed for rapid functional assignments of environmental studies. In order to assign the trait states to fungal species hypotheses, the scientific community of experts manually categorised and assigned available trait information to 697,413 fungal ITS sequences. On the basis of those sequences we were able to summarise trait and host information into 92,623 fungal species hypotheses at 1% dissimilarity threshold.

245 citations

Journal ArticleDOI
TL;DR: A high diversity of these fungi on different hosts and habitats is demonstrated and the ubiquity and diversity of the secondary root-associated fungi should be considered in studies of mycorrhizal communities to avoid overestimating the richness of true symbionts.
Abstract: Summary Mycorrhizosphere microbes enhance functioning of the plant–soil interface, but little is known of their ecology. This study aims to characterize the ascomycete communities associated with ectomycorrhizas in two Tasmanian wet sclerophyll forests. We hypothesize that both the phyto- and mycobiont, mantle type, soil microbiotope and geographical distance affect the diversity and occurrence of the associated ascomycetes. Using the culture-independent rDNA sequence analysis, we demonstrate a high diversity of these fungi on different hosts and habitats. Plant host has the strongest effect on the occurrence of the dominant species and community composition of ectomycorrhiza-associated fungi. Root endophytes, soil saprobes, myco-, phyto- and entomopathogens contribute to the ectomycorrhizaassociated ascomycete community. Taxonomically these Ascomycota mostly belong to the orders Helotiales, Hypocreales, Chaetothyriales and Sordariales. Members of Helotiales from both Tasmania and the Northern Hemisphere are phylogenetically closely related to root endophytes and ericoid mycorrhizal fungi, suggesting their strong ecological and evolutionary links. Ectomycorrhizal mycobionts from Australia and the Northern Hemisphere are taxonomically unrelated to each other and phylogenetically distant to other helotialean root-associated fungi, indicating independent evolution. The ubiquity and diversity of the secondary root-associated fungi should be considered in studies of mycorrhizal communities to avoid overestimating the richness of true symbionts.

142 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: All fungal species represented by at least two ITS sequences in the international nucleotide sequence databases are now given a unique, stable name of the accession number type, and the term ‘species hypothesis’ (SH) is introduced for the taxa discovered in clustering on different similarity thresholds.
Abstract: The nuclear ribosomal internal transcribed spacer (ITS) region is the formal fungal barcode and in most cases the marker of choice for the exploration of fungal diversity in environmental samples. Two problems are particularly acute in the pursuit of satisfactory taxonomic assignment of newly generated ITS sequences: (i) the lack of an inclusive, reliable public reference data set and (ii) the lack of means to refer to fungal species, for which no Latin name is available in a standardized stable way. Here, we report on progress in these regards through further development of the UNITE database (http://unite.ut.ee) for molecular identification of fungi. All fungal species represented by at least two ITS sequences in the international nucleotide sequence databases are now given a unique, stable name of the accession number type (e.g. Hymenoscyphus pseudoalbidus|GU586904|SH133781.05FU), and their taxonomic and ecological annotations were corrected as far as possible through a distributed, third-party annotation effort. We introduce the term ‘species hypothesis’ (SH) for the taxa discovered in clustering on different similarity thresholds (97–99%). An automatically or manually designated sequence is chosen to represent each such SH. These reference sequences are released (http://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and in the QIIME pipeline. The system and the data will be updated automatically as the number of public fungal ITS sequences grows. We invite everybody in the position to improve the annotation or metadata associated with their particular fungal lineages of expertise to do so through the new Web-based sequence management system in UNITE.

2,605 citations

Journal ArticleDOI
TL;DR: The results illustrate the importance of parameter tuning for optimizing classifier performance, and the recommendations regarding parameter choices for these classifiers under a range of standard operating conditions are made.
Abstract: Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated “novel” marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

2,475 citations

Journal ArticleDOI
28 Nov 2014-Science
TL;DR: Diversity of most fungal groups peaked in tropical ecosystems, but ectomycorrhizal fungi and several fungal classes were most diverse in temperate or boreal ecosystems, and manyfungal groups exhibited distinct preferences for specific edaphic conditions (such as pH, calcium, or phosphorus).
Abstract: Fungi play major roles in ecosystem processes, but the determinants of fungal diversity and biogeographic patterns remain poorly understood. Using DNA metabarcoding data from hundreds of globally distributed soil samples, we demonstrate that fungal richness is decoupled from plant diversity. The plant-to-fungus richness ratio declines exponentially toward the poles. Climatic factors, followed by edaphic and spatial variables, constitute the best predictors of fungal richness and community composition at the global scale. Fungi show similar latitudinal diversity gradients to other organisms, with several notable exceptions. These findings advance our understanding of global fungal diversity patterns and permit integration of fungi into a general macroecological framework.

2,346 citations

Journal ArticleDOI
TL;DR: Fungi typically live in highly diverse communities composed of multiple ecological guilds, and FUNGuild is a tool that can be used to taxonomically parse fungal OTUs by ecological guild independent of sequencing platform or analysis pipeline.

2,290 citations

Journal ArticleDOI
27 Nov 2014-Nature
TL;DR: Recent progress in understanding belowground biodiversity and its role in determining the ecological and evolutionary responses of terrestrial ecosystems to current and future environmental change are reviewed.
Abstract: Evidence is mounting that the immense diversity of microorganisms and animals that live belowground contributes significantly to shaping aboveground biodiversity and the functioning of terrestrial ecosystems. Our understanding of how this belowground biodiversity is distributed, and how it regulates the structure and functioning of terrestrial ecosystems, is rapidly growing. Evidence also points to soil biodiversity as having a key role in determining the ecological and evolutionary responses of terrestrial ecosystems to current and future environmental change. Here we review recent progress and propose avenues for further research in this field.

2,074 citations